https://github.com/dailystudio/gemini-codelab-bwa-04-12
A dedicated codelab for Gemini CodeLab of Build with AI on Apr. 12, 2025
https://github.com/dailystudio/gemini-codelab-bwa-04-12
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A dedicated codelab for Gemini CodeLab of Build with AI on Apr. 12, 2025
- Host: GitHub
- URL: https://github.com/dailystudio/gemini-codelab-bwa-04-12
- Owner: dailystudio
- License: apache-2.0
- Created: 2025-03-17T01:57:09.000Z (3 months ago)
- Default Branch: main
- Last Pushed: 2025-03-19T02:27:47.000Z (3 months ago)
- Last Synced: 2025-03-19T03:26:57.745Z (3 months ago)
- Language: Kotlin
- Size: 4.88 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Code Lab of Gemini on Android
This project is a code lab to showcase the integration and usage of Gemini SDKs on Android, including real-time interactions and performance evaluation. It demonstrates capabilities such as leveraging **Google AI Client SDK** and **MediaPipe** for LLM processing, providing a comprehensive look at Gemini technology on Android.
## Installation and Usage
### Prerequisites
- Android Studio (latest version recommended).
- Minimum Android API Level 21.
### Installation Steps
#### General Steps
1. Clone the repository:
```bash
git clone
```
2. Open the project in Android Studio.
3. Sync the Gradle files to install dependencies.
4. Build and run the application on an emulator or physical device.
#### Special Steps
##### For [Google AI Client SDK](https://ai.google.dev/gemini-api/docs)
- You need to apply an API key Google AI Studio and use it to authenticate and interact with Gemini API.
- Put your API key in `core/apikey.gemini`, with format `API_KEY=`.
##### For [MediaPipe LLM](https://developers.googleblog.com/en/large-language-models-on-device-with-mediapipe-and-tensorflow-lite/)
- Download the required models manually from the [official MediaPipe repository](https://ai.google.dev/edge/mediapipe/solutions/genai/llm_inference/index#models).
- If you choose Gemma 3 1B model, place the downloaded model to `/data/local/tmp/llm/gemma3-1B-it-int4.task` on your device.
- If you choose Gemma 2 2B model, place the downloaded model to `/data/local/tmp/llm/model.bin` on your device.
### Usage Example
After installing the app, you can use it to chat with various Gemini models and attach local files for context. The app provides a flexible interface to experiment with different AI capabilities. Additionally, you can:
- Explore real-time AI-generated responses based on your prompts.
- Attach local files to enhance the AI's understanding of the context. It requires permissions for file access if using the file picker feature.
- Use the `Settings` menu to switch between different usage modes and configure parameters to suit your needs.
> **Developer Mode**
>
> Click the illustration at the top of the `About` dialog **5 times** to toggle between **User** mode and **Developer** mode. In **Developer** mode, you gain access to enhanced setting options and can track key performance metrics—such as response time, character count, and token count—directly within the app.
## Contribution
Contributions are welcome! Follow these steps:
1. Fork this repository.
2. Create a branch: `git checkout -b feature/`.
3. Commit your changes: `git commit -m '`.
4. Push to the branch: `git push origin feature/`.
5. Create a Pull Request.
## Contact
For questions or suggestions, feel free to reach out:
- [[email protected]](mailto\:[email protected])
## License
This project is distributed under the [Apache 2.0 License](./LICENSE).